A vision for better memory profiling with about:memory

I’ve been doing lots of memory profiling of Firefox. I’ve mostly used Massif and about:memory for this. Both have their uses, but also big problems. I have some ideas for combining their best features into a killer profiling tool.

Massif’s pros and cons

I’ve mostly used Massif. It’s both invaluable and a total pain. More specifically, it has the following advantages:

Time series. It shows how memory consumption changes over time, both graphically (for total allocations) and with periodic detailed snapshots.

Level of detail. Each detailed snapshot consists of an allocation tree that shows which parts of the code are responsible for every single byte allocated.

It’s not easy to use. The command-line needed to get good results with Firefox is huge.

There’s little control over when snapshots occur. That could be improved relatively easily with client requests, though they require code modifications so they’re a bit painful.

The superblock allocation problem. You can profile with Massif at the OS page level, or at the heap (malloc) level. In both cases, the results can be misleading because an allocation request doesn’t always result in a visible allocation occurring. For example, if profiling at the OS page level, most calls to malloc won’t result in pages being allocated with mmap, because when jemalloc needs pages from the OS it will usually request more than necessary for the current request, and then hand out pieces of those pages itself on subsequent calls to malloc. If profiling at the heap level, this problem also occurs with custom allocators such as JSArenaPool that are layered on top of malloc. As a result, many allocation requests don’t get recorded by Massif, and a small number of them are blamed for allocating much more memory than they actually did. (The whole question of “what level do I measure at?” is one of the trickiest things about memory profiling.)

The result is that using Massif and understanding its output is difficult for anyone who isn’t an expert.

about:memory’s pros and cons

The other tool I sometimes use is about:memory. It has the following advantages:

Lightweight, trivial to view.

Full control over when measurements occur.

And the disadvantages:

Minimal data, mostly just the heap.

The values are not as easy to understand as they seem.

No time series.

A better about:memory

I want the best of both worlds: time series, detailed measurements, control when measurements occur, ease-of-use. Plus a bit more: both OS page and heap level measurements, accurate numbers, global and per-compartment measurements, and good visualizations of both snapshots and time series data. Basically, I want to re-implement a decent chunk of Massif within about:memory. What follows is a 4am braindump, apologies for the density, hopefully it’s mostly understandable.

Merge about:memory and Shaver’s nascent about:compartments, because they’re really doing the same thing.

More global measurements:

Add current and peak total memory and RSS (resident set size), as measured by the system (eg. /proc/pid/status on Linux).

Keep malloc stats as they currently are (eg. malloc/allocated).

More individual counts. Eg. for JS we currently have js/gc-heap, js/string-data, js/mjit-code. I want to split js/mjit-code into several counts: JaegerMonkey code (inline, out-of-line, ICs) and JaegerMonkey data (JITScripts and IC data). And also add counts for: TraceMonkey code and data, Shapes, JSFunctions, JSScripts, cx->tempAlloc (which holds JSParseNodes plus other things), JSFunctions, js::Vector, js::HashTable… basically anything that shows up reasonably high in Massif profiles. We currently have 19 individual counts, I imagine having 50+. Obviously there’ll be lots of non-JS counters added as well.

Allow individual counts to be shown in a standard order, or in order from biggest to smallest.

For a lot of these, both the number of bytes allocated and the number of allocations might be useful.

Per-compartment measurements: show all the individual counts, but on a per-compartment basis.

Clearer meanings of measurements:

Add links/tooltips/whatever to every measurement with a brief description so that it’s clear what it means.

Make the graph interactive, eg. allow drilling down to individual counts, going back to previous snapshots.

I have a hacky prototype canvas implementation of something like this that reads Massif’s output files. SVG would probably be better, though.

Diffs of some kind between snapshots would be great. It would allow you to answer questions like “how much memory is allocated when I open a new tab?”

If telemetry is ever implemented, sending this data back from users would be great, though that’s a lot harder.

Potential difficulties:

Not that many, as far as I can tell. A lot of the infrastructure is already in place.

Keeping the counter code up-to-date may be tricky. If it’s used frequently by many people, that’ll increase the likelihood that it’ll be kept up to date. Better descriptions will help make it clearer if the counters are counting what they’re supposed to.

about:memory will itself use some memory. It’s unclear how to avoid measuring that. Maybe putting the more advanced features like the graphical stuff in a separate about:morememory page might mitigate this; you could take a bunch of snapshots via about:memory and then open up about:morememory.

Performance… will more counters be noticeable? Hopefully not since we already have a bunch of them anyway.

“Add links/tooltips/whatever to every measurement with a brief description so that it’s clear what it means.”
about:memory items already have tooltips, although the descriptions are pretty short right now.